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International Conference on Information Security Practice and Experience

ISPEC 2015: Information Security Practice and Experience pp 109–120Cite as

Analysis of Fractional ωmbNAF for Scalar Multiplication

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9065))

Abstract

In the current work we analyze the average Hamming weight of recoded sequence obtained by fractional ωmbNAF algorithm using Markov theory. Cost comparison between fractional ωmbNAF and different scalar recoding methods is given. Regardless of memory restraint, it is shown that \(\{2,3,5\}\mbox{NAF}_{3+\frac{3}{4}}\) improves tree-based double base chain by a factor of 6.8% and 13.2% is Jacobian curves(with efficiency-orient selected parameter a = 3) and inverted Edwards curves respectively.

This work is supported in part by National Research Foundation of China under Grant No. 61272040, 61379137, and in part by National Basic Research Program of China (973) under Grant No. 2013CB338001.

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Author information

Authors and Affiliations

  1. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Weixuan Li, Wei Yu & Kunpeng Wang

  2. Data Assurance and Communication Security Research Center, Chinese Academy of Sciences, Beijing, China

    Weixuan Li, Wei Yu & Kunpeng Wang

  3. University of Chinese Academy of Sciences, Beijing, China

    Weixuan Li

Authors
  1. Weixuan Li
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  2. Wei Yu
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  3. Kunpeng Wang
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Corresponding author

Correspondence to Weixuan Li .

Editor information

Editors and Affiliations

  1. University of Malaga, Malaga, Spain

    Javier Lopez

  2. Institute for Infocomm Research, Singapore, Singapore

    Yongdong Wu

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© 2015 Springer International Publishing Switzerland

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Li, W., Yu, W., Wang, K. (2015). Analysis of Fractional ωmbNAF for Scalar Multiplication. In: Lopez, J., Wu, Y. (eds) Information Security Practice and Experience. ISPEC 2015. Lecture Notes in Computer Science(), vol 9065. Springer, Cham. https://doi.org/10.1007/978-3-319-17533-1_8

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  • DOI: https://doi.org/10.1007/978-3-319-17533-1_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17532-4

  • Online ISBN: 978-3-319-17533-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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